About
I’m an AI researcher and engineer working across machine learning, embedded intelligence, and large-scale technical infrastructure.
My work spans the full stack of modern AI systems, from embedded and hardware-integrated environments to multimodal learning, model architecture, and production ML infrastructure. I focus on building systems that are technically rigorous while remaining practical and deployable in real-world environments.
I currently work as an AI R&D Co-op at Amazon Lab126, contributing to embedded AI and multimodal systems research focused on real-world intelligent systems.
Previously, I worked as a Software Engineering Intern with a machine learning focus at Capital Technology Group, contributing to ML systems operating on large government and financial datasets for anomaly detection, trade surveillance, predictive analytics, and data-driven risk modeling.
Outside of formal research, I build independent technical systems spanning embedded platforms, scalable infrastructure, intelligent data pipelines, and applied AI products.
Some of the systems I’m currently developing are not public yet. When they are, they’ll appear here.
Updates
Current Focus
Conducting embedded AI and multimodal systems research through Amazon Lab126 while advancing independent technical initiatives across machine learning, intelligent systems, audio interfaces, and scalable data-driven infrastructure. Current work focuses on agentic voice technologies, adaptive human-device interaction, and next-generation AI systems designed for real-world deployment.
- Embedded AI & Amazon Lab126 R&D
- Multimodal systems and applied ML research
- Private ventures and infrastructure development